Hi, Is this a bug or the cache is designed to work this way?
If it is as-designed, can this behavior be updated in ignite documentation? Thanks, Prasad On Wed, Oct 30, 2019 at 7:19 PM Ilya Kasnacheev <[email protected]> wrote: > Hello! > > I have discussed this with fellow Ignite developers, and they say read > through for replicated cache would work where there is either: > > - writeThrough enabled and all changes do through it. > - database contents do not change for already read keys. > > I can see that neither is met in your case, so you can expect the behavior > that you are seeing. > > Regards, > -- > Ilya Kasnacheev > > > вт, 29 окт. 2019 г. в 18:18, Akash Shinde <[email protected]>: > >> I am using Ignite 2.6 version. >> >> I am starting 3 server nodes with a replicated cache and 1 client node. >> Cache configuration is as follows. >> Read-through true on but write-through is false. Load data by key is >> implemented as given below in cache-loader. >> >> Steps to reproduce issue: >> 1) Delete an entry from cache using IgniteCache.remove() method. (Entry >> is just removed from cache but present in DB as write-through is false) >> 2) Invoke IgniteCache.get() method for the same key in step 1. >> 3) Now query the cache from client node. Every invocation returns >> different results. >> Sometimes it returns reloaded entry, sometime returns the results >> without reloaded entry. >> >> Looks like read-through is not replicating the reloaded entry on all >> nodes in case of REPLICATED cache. >> >> So to investigate further I changed the cache mode to PARTITIONED and set >> the backup count to 3 i.e. total number of nodes present in cluster (to >> mimic REPLICATED behavior). >> This time it worked as expected. >> Every invocation returned the same result with reloaded entry. >> >> * private CacheConfiguration networkCacheCfg() {* >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> * CacheConfiguration networkCacheCfg = new >> CacheConfiguration<>(CacheName.NETWORK_CACHE.name >> <http://CacheName.NETWORK_CACHE.name>()); >> networkCacheCfg.setAtomicityMode(CacheAtomicityMode.TRANSACTIONAL); >> networkCacheCfg.setWriteThrough(false); >> networkCacheCfg.setReadThrough(true); >> networkCacheCfg.setRebalanceMode(CacheRebalanceMode.ASYNC); >> networkCacheCfg.setWriteSynchronizationMode(CacheWriteSynchronizationMode.FULL_SYNC); >> //networkCacheCfg.setBackups(3); >> networkCacheCfg.setCacheMode(CacheMode.REPLICATED); >> Factory<NetworkDataCacheLoader> storeFactory = >> FactoryBuilder.factoryOf(NetworkDataCacheLoader.class); >> networkCacheCfg.setCacheStoreFactory(storeFactory); >> networkCacheCfg.setIndexedTypes(DefaultDataAffinityKey.class, >> NetworkData.class); networkCacheCfg.setSqlIndexMaxInlineSize(65); >> RendezvousAffinityFunction affinityFunction = new >> RendezvousAffinityFunction(); >> affinityFunction.setExcludeNeighbors(false); >> networkCacheCfg.setAffinity(affinityFunction); >> networkCacheCfg.setStatisticsEnabled(true); // >> networkCacheCfg.setNearConfiguration(nearCacheConfiguration()); return >> networkCacheCfg; }* >> >> @Override >> public V load(K k) throws CacheLoaderException { >> V value = null; >> DataSource dataSource = springCtx.getBean(DataSource.class); >> try (Connection connection = dataSource.getConnection(); >> PreparedStatement statement = >> connection.prepareStatement(loadByKeySql)) { >> //statement.setObject(1, k.getId()); >> setPreparedStatement(statement,k); >> try (ResultSet rs = statement.executeQuery()) { >> if (rs.next()) { >> value = rowMapper.mapRow(rs, 0); >> } >> } >> } catch (SQLException e) { >> >> throw new CacheLoaderException(e.getMessage(), e); >> } >> >> return value; >> } >> >> >> Thanks, >> >> Akash >> >>
